getpacket.wp | R Documentation |
This function extracts and returns a packet of coefficients from a wavelet packet (wp
) object.
## S3 method for class 'wp'
getpacket(wp, level, index, ... )
wp |
Wavelet packet object from which you wish to extract the packet from. |
level |
The resolution level of the coefficients that you wish to extract. |
index |
The index number within the resolution level of the packet of coefficients that you wish to extract. |
... |
any other arguments |
The wp
produces a wavelet packet object. The coefficients in this structure can be organised into a binary tree with each node in the tree containing a packet of coefficients.
Each packet of coefficients is obtained by chaining together the effect of the two packet operators DG and DH: these are the high and low pass quadrature mirror filters of the Mallat pyramid algorithm scheme followed by decimation (see Mallat~(1989b)).
Starting with data c^J
at resolution level J containing
2^J
data points the wavelet packet algorithm operates as follows.
First DG and DH are applied to c^J
producing
d^{J-1}
and c^{J-1}
respectively.
Each of these sets of coefficients is of length one half of the original data:
i.e. 2^{J-1}
.
Each of these sets of coefficients is a set of
wavelet packet coefficients.
The algorithm then applies both DG and DH to both
d^{J-1}
and c^{J-1}
to form a four sets of coefficients at level
J-2. Both operators are used again on the four sets to produce 8 sets, then again on the 8 sets to form 16 sets and so on. At level j=J,...,0 there are
2^{J-j}
packets of coefficients each containing 2^j
coefficients.
This function enables whole packets of coefficients to be extracted at any resolution level. The index argument chooses a particular packet within each level and thus ranges from 0 (which always refer to the father wavelet coefficients), 1 (which always refer to the mother wavelet coefficients) up to 2^{J-j}
.
A vector containing the packet of wavelet packet coefficients that you wished to extract.
Version 3.9 Copyright Guy Nason 1998
G P Nason
wp
, putpacket.wp
, basisplot.wp
, draw.wp
, InvBasis.wp
, MaNoVe.wp
, nlevelsWT.wp
, plot.wp
. threshold.wp
.
#
# Take the wavelet packet transform of some random data
#
MyWP <- wp(rnorm(1:512))
#
# The above data set was 2^9 in length. Therefore there are
# coefficients at resolution levels 0, 1, 2, ..., and 8.
#
# The high resolution coefficients are at level 8.
# There should be 256 DG coefficients and 256 DH coefficients
#
length(getpacket(MyWP, level=8, index=0))
#[1] 256
length(getpacket(MyWP, level=8, index=1))
#[1] 256
#
# The next command shows that there are only two packets at level 8
#
## Not run: getpacket(MyWP, level=8, index=2)
#Index was too high, maximum for this level is 1
#Error in getpacket.wp(MyWP, level = 8, index = 2): Error occured
#Dumped
#
# There should be 4 coefficients at resolution level 2
#
# The father wavelet coefficients are (index=0)
getpacket(MyWP, level=2, index=0)
#[1] -0.9736576 0.5579501 0.3100629 -0.3834068
#
# The mother wavelet coefficients are (index=1)
#
#[1] 0.72871405 0.04356728 -0.43175307 1.77291483
#
# There will be 127 packets at this level.
#
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